A Closed-Loop Method to Identify EMG-Torque Dynamics in Human Balance Control
Bibliographic record
Abstract
Human balance control requires continuous modulation of ankle torque by central and spinal activation of the ankle muscles combined with the intrinsic mechanical stiffness of the joint. These components appear together and cannot be measured separately. This work presents a novel multiple-input, single-output, closed-loop identification method that decomposes the ankle torque in human balance control into its central, stretch reflex, and intrinsic components. The method models separate transfer functions for each EMG-torque relation for central and stretch reflex mechanisms and estimates the ankle intrinsic torque from the residuals. The method uses only EMG measurements, requires no kinematic data, and has few parameters, resulting in robust performance. Application of the method to perturbed standing data from two healthy subjects demonstrated that the central and stretch reflex torques accounted for 80-93% of the ankle torque variation, while the intrinsic stiffness was responsible for most of the remaining torque.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".